Navigation with regard to temporally-spatially variable event

Abstract

The invention relates to a navigation method, in which a navigation device calculates a navigation route (20) from a starting location to a destination. The navigation method according to the invention is characterised in that: - a computing unit obtains information regarding at least one temporally and spatially variable event (1); - the computing unit estimates a temporal and spatial course of the event (1) for a future time horizon and stores it as a dynamic area of ​​interest (2); - the navigation device determines a starting location and a starting time, receives the dynamic area of ​​interest (2) and calculates the navigation route (20) from the starting location to the destination, the destination being within the dynamic area of ​​interest (2) or an observation point (3) from which the event (1) can be observed being set as the destination.

Description

[0001] NAVIGATION TO A TIME- AND LOCALLY VARIABLE EVENT

[0002] The invention relates to a navigation method according to the type defined in more detail in the preamble of claim 1 and to a navigation system according to the type defined in more detail in the preamble of claim 7.

[0003] With the help of a navigation device, a user can orient themselves more easily, especially in unfamiliar surroundings. A navigation route can be determined from a starting point to a destination, showing the user the route to follow. Navigation devices can be permanently integrated into a vehicle or be mobile, for example, as a dedicated mobile device or as an application running on a smartphone.

[0004] The user can specify the destination manually. To further assist the user, the navigation device can also make its own destination suggestions. For this purpose, the navigation device can access a list of points of interest (POIs), which are a collection of locations frequently visited in everyday life. These include, for example, public parking lots, doctor's offices, shopping centers, gas stations, restaurants, and the like. A POI can also be designed as a flat area and have several specific access points that can be set as navigation destinations.

[0005] DE 102008 007642 A1 discloses a navigation device with time-dependent POI display. The navigation device is able to assign an opening time to each POI and, taking into account the current time or the arrival time at the POI, determine whether the POI is open and thus usable or not. Unusable POIs can be hidden from the map display on the navigation device, which improves clarity. Furthermore, it is known to update the list of available POIs in a region. This allows POIs that no longer exist to be removed, for example, the opening hours of an existing POI can be adjusted, and new POIs can be added to the list. The navigation device can obtain corresponding information from an external source, for example via the Internet or a portable computer-readable storage medium connected to the navigation device.The update can be performed as needed or can be accompanied by an update of the map data used. Temporary but fixed events, such as a sporting event or a festival, can also be temporarily accessible as POIs and set as destinations.

[0006] In addition, a navigation device can obtain current traffic information and take current road closures, diversions and / or traffic jams into account when calculating a navigation route.

[0007] However, there is further potential for determining navigation routes for users, which remains untapped.

[0008] Furthermore, US 2020 / 0408545 A1 discloses navigation to a moving target. The target transmits its current location, a current time, and a direction of movement using a navigation device. Based on a path of several target locations and context information, a future location of the target is estimated, and a navigation route is determined to arrive at such a future location at the same time as the target.

[0009] Furthermore, DE 102023 004 236 A1 discloses a method for navigating a vehicle. The vehicle is navigated to a moving destination. The geocoordinates of the destination are transmitted via a navigation interface.

[0010] Furthermore, WO 2010 / 086680 A1 discloses a navigation system for determining a navigation route to a moving destination. A server receives information about the changing location of a moving destination. The server sends the information to a GPS transceiver. A navigation route is calculated from the location of the GPS transceiver to the moving destination. Furthermore, US 2012 / 0239584 A1 discloses navigation to a dynamic endpoint.

[0011] Furthermore, US 2022 / 0113721 A1 discloses collaborative travel.

[0012] In addition, US 2007 / 0100539 A1 discloses a method for determining a destination based on an identification feature of a moving object and a method for providing position information.

[0013] The present invention is based on the object of providing an improved navigation method which further improves user interaction compared to the prior art.

[0014] According to the invention, this object is achieved by a navigation method having the features of claim 1. Advantageous embodiments and further developments as well as a navigation system for implementing the method emerge from the dependent claims.

[0015] A generic navigation method, in which a navigation device calculates a navigation route from a starting point to a destination, provides that

[0016] - a computing unit obtains information about at least one temporally and spatially variable event;

[0017] - the computing unit estimates a temporal and spatial course of the event for a future time horizon and stores it as a dynamic area of ​​interest;

[0018] - the navigation device receives the dynamic area of ​​interest, sets a starting location and a starting time and calculates the navigation route from the starting location to the destination, whereby the destination lies within the dynamic area of ​​interest or an observation point is set as the destination from which the event can be observed,

[0019] - the computing unit divides a digital road map into a plurality of polygons, each polygon being assigned map information so that the polygons represent the digital road map in the form of a dynamic graph and the computing unit maps the dynamic area of ​​interest onto the dynamic graph, the dynamic graph comprising a plurality of nodes, each polygon being assigned a node.

[0020] According to the invention, it is provided that the nodes of the graph are assigned height information as map information, wherein the height information describes the topographical height of the terrain and / or the geodetic height of an object located in the respective polygon, and the computing unit calculates a height difference to the respective neighboring nodes for each node of the graph, wherein a clear view to a neighboring node exists if the height to the neighboring node remains the same or decreases; and wherein the computing unit determines a node chain emanating from the dynamic area of ​​interest with a clear view of the dynamic area of ​​interest and defines a node of the node chain as an observation point.

[0021] Compared to the prior art, the navigation method according to the invention makes it possible for the first time to set dynamic events as destinations for a navigation route in addition to taking static events into account. A dynamic event differs from a static event in that the location of the event changes over time. This therefore represents a particularly complex scenario for calculating a navigation route, as the navigation route must be determined over time due to the changing destination. Furthermore, the navigation method according to the invention makes it possible not only to locate the dynamic area of ​​interest (AOI), but also to observe it. For this purpose, the navigation device is capable of calculating a navigation route to an observation point, i.e., a point that may be located far away from the actual destination.This opens up a completely new scope for route suggestions for navigation device users. The observation point can, in the broadest sense, also be an area, i.e., an observation line or observation area.

[0022] The computing unit can be integrated into the navigation device or implemented externally, for example as a cloud server. The computing unit can obtain information about temporally and spatially variable events from various sources, which will be discussed in more detail below. A wide variety of temporally and spatially variable events can be taken into account. These include, in particular, periodically recurring events such as sunrise, sunset, a solar eclipse, moonrise, moonset, low tide, high tide, and the like. Furthermore, these include events with a specific time window, such as the northern lights, whale sightings, algal blooms, the appearance of plankton that glows self-luminously due to bioluminescence, a herd of elephants moving through a specific area, and the like.

[0023] There are various ways in which the computing unit can estimate the temporal and spatial progression of the respective event for the future time horizon. The future time horizon is specific for each event and corresponds to the respective period of occurrence. For example, sunrise and sunset occur at different times every day depending on the date and the latitude and longitude on the Earth's surface. The occurrence of the Northern Lights depends in particular on the season and solar activity. One opportunity to observe whales depends on the migratory behavior of the whales and is therefore also seasonal. The temporal and spatial progression can be read from the information obtained by the computing unit itself, should it be contained in this information.However, the computing unit can also determine the temporal and spatial progression itself, for example, taking historical data into account or based on mathematical calculations. Certain events, such as the aforementioned whale migrations, occur seasonally, so they follow certain identifiable patterns. Periodic events such as sunrise, a solar eclipse, or the tides can be calculated using deterministic equations. Specific events, however, can change unpredictably, requiring special measures to estimate the temporal and spatial progression, which will be discussed in more detail below.

[0024] The navigation device receives a respective dynamic area of ​​interest from the processing unit. In particular, a comprehensive list of all currently available dynamic areas of interest can be transmitted to the navigation device, and a respective dynamic area of ​​interest can be proactively output by the navigation device for a route suggestion to the user of the navigation device. This can occur, for example, when the user uses the navigation device. In particular, the starting location corresponds to the current location of the navigation device, which the navigation device can determine in a proven manner, for example, using a global navigation satellite system such as GPS, Galileo, or the like.Location determination can also be performed using triangulation, for example, by evaluating the cellular signal strength of at least three cellular network base stations within communication range. The navigation device can also be capable of identifying characteristic landscape features, with corresponding camera images being provided, for example, by a vehicle's surround-view camera. In this case, the start time corresponds to the current time.

[0025] It is also possible for the user of the navigation device to plan a navigation route in advance, for example for the next day, the next week, or another future day. A point in time within the corresponding time window is then selected as the start time. For example, the user of the navigation device may be on vacation and is planning an activity for the evening or the next day. In this case, the navigation device can make suggestions for visiting or participating in the time- and location-changing event or the dynamic area of ​​interest. If the user plans the navigation route for a future day, the navigation device can only then query the processing unit for information relating to time- and location-changing events specifically for this time window. This enables efficient use of memory within the navigation device, since only relevant information needs to be retrieved and stored locally.

[0026] In general, the starting location can also be specified manually by the user, which makes planning future trips even easier. This way, the user knows that, for example, they will be in a different location in a few days. The navigation device can also specify the starting location and start time itself. For example, the navigation device can access the user's digital calendar and calculate a navigation route based on a read-out calendar entry. The dynamic area of ​​interest can also be suggested as an intermediate destination for a navigation route determined to another destination, and the dynamic area of ​​interest or observation point can be selected as the new (intermediate) destination. It is sufficient if the navigation device receives and suggests dynamic areas of interest that lie along the route or observation point originally planned by the user.can be reached depending on the starting location and starting time. This further reduces the communication requirements with the computing unit, making the process of the invention even more efficient.

[0027] Various methods can be used to calculate the observation point, which will be discussed below.

[0028] As already described, the computing unit divides a digital road map into a plurality of polygons, in particular symmetrical polygons, with map information being assigned to each polygon, so that the polygons represent the digital road map in the form of a dynamic graph, and the computing unit maps the dynamic area of ​​interest onto the dynamic graph. This enables the digital road map to be discretized in the form of a dynamic graph. This enables the provision of additional functions, which will be discussed in more detail below. "Road map" in this context means any form of digitally available map, preferably comprising the course of a road network.

[0029] The polygons can take on any imaginable shape and size. The polygons can be asymmetrical or symmetrical, for example. They can be triangles, rectangles, or other shapes that fill the plane. Different shapes can also be combined. Preferably, they are exclusively squares. The resolution or size of the polygons can also be dependent on the location. For example, a higher resolution can be used in populated regions such as cities and the resolution can be reduced in uninhabited rural areas. As map information, information about POIs, AOIs, streets or road types, traffic regulations, weather, visibility conditions, and the like can be stored, i.e. assigned, in the respective polygons.

[0030] A graph is an ordered pair of a set of vertices and a set of edges. Different types of graphs are known, such as: undirected graphs without multiple edges, directed graphs without multiple edges, undirected graphs with combined multiple edges, directed graphs with combined multiple edges, directed graphs with independent multiple edges, and so-called hypergraphs. The polygons of the road map represent the nodes of the graph. Neighboring polygons are connected by edges. The dynamic areas of interest are annotated on the nodes. A navigation route can also be mapped to the graph using additional annotations.

[0031] Dynamic graphs are time-varying graphs. The topography and / or labels of individual components of the graph can change. These changes are also referred to as "evolution." By implementing the digital road map as a dynamic graph, dynamic areas of interest can be mathematically mapped particularly efficiently onto a digital road map. In particular, it allows the use of computational models known from graph theory to offer a wide variety of functions available in connection with dynamic areas of interest.

[0032] As already described, elevation information is assigned to the nodes of the graph as map information. The elevation information describes the topographical elevation of the terrain and / or the geodetic elevation of an object located in the respective polygon. The computing unit calculates an elevation difference to the respective neighboring nodes for each node of the graph. A clear view to a neighboring node exists if the elevation to the neighboring node remains the same or decreases. Corresponding elevation information can already be contained in topographical maps or can also be obtained from other external sources. Taking the topographical elevation into account, the computing unit can thus determine whether, for example, a hill or mountain blocks the view of a dynamic area of ​​interest.There may also be objects in a corresponding polygon that can block the view, such as particularly tall trees, high-rise buildings, walls or the like.

[0033] If there are several elevated objects within a polygon, an average height across all objects can be determined as height information, or the height of the tallest object in the polygon can be used as height information. The object's extension in the plane can also be used as a reference value to determine when the object's height should be considered. The extension can be determined as an absolute value or as a percentage of the total area of ​​the respective polygon. This allows a user to "look past" a thin tree or a tall lamppost without any doubt, eliminating the need to consider any obstructions to such objects.

[0034] In particular, information about elevated objects can be collected and provided by the vehicles in the fleet. This allows the height and, if applicable, the extent of an object in the plane to be estimated from the camera images generated by one or more surrounding cameras. For this purpose, information captured using stereo cameras or by comparing the camera images with reference objects can be used. Furthermore, the objects can be scanned with sensors that allow the generation of depth information, such as LiDARe.

[0035] The computing unit determines a chain of nodes emanating from the dynamic area of ​​interest with a clear view of the dynamic area of ​​interest and defines a node in the chain as an observation point. Starting from the dynamic area of ​​interest, the computing unit checks which chains of nodes allow a clear view of the dynamic area of ​​interest. To do this, the height difference between the respective neighboring nodes is evaluated. From the dynamic area of ​​interest, radially outward-extending chains of nodes can then be formed on the graph. Their perimeter is formed by the first pair of nodes, where the height increases towards the dynamic area of ​​interest. Observation points can then be located within the area thus formed.

[0036] This procedure can be repeated at different points in time, as the dynamic area of ​​interest has moved further, allowing different observation points to be found at different times. This also makes it possible to find observation points that do not correspond to usual POIs. For example, a point on a country road from which a bay can be seen can be selected as the observation point. This enables whale watching, for example. Observation points can also be understood as observation lines or observation areas. For example, the dynamic area of ​​interest can be observable for a specific period of time along a section of the country road. In the case of a herd of elephants, it may also be possible to designate a specific area as the observation area, as the elephants can be observed from a great distance from different points, for example in a savannah.

[0037] To calculate the navigation route to be output, a spatial-temporal intersection is calculated between the trajectory of the dynamic area of ​​interest and possible navigation routes. The intersection of this set forms the set of nodes that represent a possible observation point.

[0038] An advantageous development of the navigation method according to the invention further provides that the computing unit stores information about temporally and spatially variable events in an event database, wherein for each event at least the following is stored:

[0039] - whether the event can be visited and / or observed; and

[0040] - when and where the event takes place.

[0041] With the help of the event database, it is possible to store information about temporally and spatially variable events and thus dynamic areas of interest within the processing unit, so that this information does not have to be retrieved from the external source for each request. The processing unit can also predict the temporal and spatial course of the event itself, as already described, and add corresponding information to the event database. In this way, further information concerning a specific event can be gradually collected and aggregated. Based on the information regarding whether the event can be visited and / or observed, the navigation device can be informed whether the dynamic area of ​​interest itself and / or the observation point should be determined as the destination.If both are possible, the navigation device user can be asked whether they want to visit the dynamic area of ​​interest or view it from a distant observation point. For example, a sunrise, a lunar eclipse, or the northern lights can be viewed from one observation point, while a passing herd of elephants or luminous plankton can be viewed locally. Common points of interest, or POIs, can be suggested as destinations as observation points, but these are determined taking into account the temporal and spatial course of the changing event. For example, a sunrise or a herd of whales can be particularly well observed from a vantage point.In a particularly simple embodiment of the method according to the invention, common points of interest such as parking spaces in the vicinity of the dynamic area of ​​interest can be determined and, for example, the nearest points of interest can be determined as observation points.

[0042] If the dynamic area of ​​interest itself is determined as the destination, any point within the dynamic area of ​​interest, for example along a road or even an off-road point, can be determined as the exact destination.

[0043] For example, the geometric center of the dynamic area of ​​interest can be selected as the destination. If the event involves self-luminous plankton, for example, any point along a stretch of beach where the luminous plankton is present at that time can be suggested as the destination. However, proven POIs can also be considered here, so if there is a nearby parking lot, the parking lot itself can be set as the destination.

[0044] Further information can be stored in the event database, such as in particular an event class, preferably divided into periodic events and events with a specific occurrence window, a method for detecting the event in the information obtained from the external source, a method for calculating or estimating the temporal development of the event or the observation point or an observation area, a method of depicting it on a map, or other information, such as the requirement to bring bathing suits, which, for example, allows the user to be immersed in the self-luminous plankton.

[0045] According to a further advantageous embodiment of the navigation method according to the invention, the computing unit obtains current information about temporally and spatially variable events from at least one of the following sources:

[0046] - a vehicle of a networked vehicle fleet; - a satellite, wherein the satellite provides aerial photographs showing at least a portion of the dynamic area of ​​interest;

[0047] - a social network, where posts about the event are shared on the social network; and / or

[0048] - a service provider.

[0049] Information about periodically occurring, temporally and spatially variable events can preferably be stored locally in the navigation device or the processing unit. This allows the navigation device to independently determine, based on deterministic rules, when and where, for example, a sunset can be observed. As already mentioned at the beginning, however, further measures may be necessary to observe or locate temporally and spatially variable events with a specific occurrence window. Current information may be required, which can be obtained, in particular, from the sources mentioned above.

[0050] In particular, the vehicles in a fleet can form a kind of mobile sensor that collects information about the temporally and spatially variable event. To do this, the corresponding vehicles can record environmental information using internal and external sensors and send it to a central location for analysis. For example, vehicles can capture images of the environment using environmental cameras and also record sounds using external microphones.

[0051] For example, the passing of a parade, such as a carnival parade, can be detected using vehicles parked at the side of the road. A cloud server, for example, evaluating the relevant information provided by the vehicles, can determine the current position of a particular float. An external service provider, such as the parade planning agency, could simultaneously obtain the parade route and, taking into account the speed of the float, estimate when and where along the parade route a particular float will be.

[0052] The method according to the invention thus allows the provision of the following function: In an input mask, for example, displayed on the navigation device or, in the case of an in-vehicle navigation device, on a touch-sensitive display in the vehicle, the user could select the individual floats of the parade and have suggestions displayed as to where and when the user should be along the parade route in order to view the desired float. In particular, available parking spaces in the vicinity can be taken into account, as well as the corresponding walking distance from the parking lot to the parade route, so that the user can arrive at the desired location on time.

[0053] Certain events, such as a passing herd of elephants, can also be analyzed particularly reliably and easily using satellite images. Elephants can be identified in satellite aerial photographs, and their current location can be determined. For this purpose, the corresponding aerial photographs can also be evaluated automatically, for example, using well-known image recognition algorithms, preferably using artificial intelligence. This also allows the temporal and spatial development of the resulting dynamic area of ​​interest to be estimated. For example, aerial photographs taken one after the other can be compared, and by tracking individual elephants, the direction and speed of movement of the elephants can be estimated. This information can be projected into the future, allowing the elephants' future location to be determined.

[0054] Furthermore, information about specific events can be obtained from social networks. This means that users of the social network can already be present at a temporally and spatially variable event and share posts about it. The posts can also be enhanced with photos, for example, taken with a smartphone. Geocoordinates of the event, in particular the camera image, can also be included in a corresponding post. This makes it possible to determine and estimate the current location or area of ​​the temporally and spatially variable event, taking into account the respective geocoordinates of the respective posts, which change over time. Corresponding information can be obtained from social networks in a proven way. In particular, so-called web crawlers can be used for this purpose.Such programs can also be based on the use of artificial intelligence, particularly artificial neural networks. Information about temporally and spatially variable events can also be obtained from a service provider. This could be a weather service or a space agency, for example. Information about solar storms and the resulting aurorae can be obtained. This can then be used to estimate where and when the aurorae will occur. For example, if the user of the navigation device is on vacation in northern Sweden in winter and uses the vehicle to do some shopping at midday, the navigation device can display a notification that the aurorae will occur in the evening or at night due to a sunspot maximum. The navigation device then suggests corresponding observation points near the user's vacation destination as destinations.This allows the user to plan a new activity for the evening that was previously completely unknown to them. Observation points can be suggested that offer particularly good views of the Northern Lights and / or can be reached within a short travel time.

[0055] The data exchange between the external sources and the computing unit can take place in a tried and tested manner, in particular using common interfaces such as APIs. If the computing unit is a cloud server, the corresponding information can be obtained via the Internet, for example. If the computing unit is part of the navigation device, the navigation device can have a connection to the Internet, in particular using a cellular connection, and thus also obtain information from the external sources. The computing unit can also be another internal vehicle computing unit. The vehicle can have a telecommunications unit, which can also be used to establish a connection to the Internet via cellular network or, if a Wi-Fi hotspot is within range, via a WLAN connection.

[0056] According to a further advantageous embodiment of the navigation method according to the invention, the computing unit determines several potential observation points, and the observation point designated as the destination is selected manually by a user or automatically by the computing unit, such that the travel time and / or distance from the starting point to the destination is minimized, in particular taking into account the observation point as an intermediate destination. The user is thus able to proactively have the navigation device suggest dynamic areas of interest and select these as the destination. The user can freely select the starting point and start time, so that a large selection of destinations can be determined. The user can thus manually select when and where they wish to visit or observe the temporally and spatially variable event. However, the computing unit can also make this selection independently.This is particularly the case if the user programs a different navigation route into the navigation device, whereupon the navigation device suggests corresponding dynamic areas of interest as intermediate destinations. Dynamic areas of interest that can be reached while driving along the original route can be suggested as intermediate destinations. If various observation points are possible, the computer unit or the navigation device selects the point for which the travel distance and / or travel time is minimal, or suggests such a point separately. This enables a particularly rapid arrival at the dynamic area of ​​interest or observation point.

[0057] A further advantageous embodiment of the navigation method further provides that the navigation device recalculates the navigation route during the journey to the destination, in particular taking into account an updated dynamic area of ​​interest. The recalculation of navigation routes is already well known in the art. For example, an alternative route can be calculated due to a road closure or traffic jam. However, these always involve static boundary conditions. According to the invention, however, the dynamic area of ​​interest moves, which makes the recalculation of the navigation route correspondingly challenging. Thus, it is important not only to consider the current traffic situation or boundary conditions for navigation route planning, but also the temporal development of the location of the dynamic area of ​​interest.According to the invention, these two boundary conditions are taken into account equally, which allows the navigation route to be determined particularly reliably.

[0058] According to a further advantageous embodiment of the navigation method according to the invention, the navigation device proactively suggests to a user the search for or observation of a temporally and spatially variable event represented by a dynamic area of ​​interest, in particular taking into account a user preference, wherein the user preference describes a preferred event category by the user. As already mentioned, the user can thus be made suggestions for activities that the user would otherwise not have considered. The user can specify user preferences regarding which event categories should be automatically suggested, such as whale watching or observing the Northern Lights. This ensures an enhanced user experience. Suggestions that the user would not accept can thus be omitted.To enter user preferences, the user can use any proven human-machine interface, such as a touch-sensitive display device.

[0059] In a navigation system comprising at least one navigation device, in particular an in-vehicle navigation device, according to the invention the navigation device is configured to carry out a method described above. The computing unit can be integrated into the navigation device. The computing unit can also be integrated into a corresponding vehicle. The computing unit can also be a vehicle-external computing device such as a cloud server. In addition to the navigation device, the navigation system can therefore also comprise a computing unit external to the navigation device. The computing unit has corresponding interfaces for obtaining information about events that vary over time and location. In particular, corresponding information can be obtained via an API over the Internet.

[0060] The computing unit and the navigation device each comprise a computer-readable storage medium having a computer program product, the execution of which on a processor allows the provision of the method steps to be carried out by the respective component according to the method according to the invention.

[0061] Further advantageous embodiments of the navigation method according to the invention also emerge from the exemplary embodiments which are described in more detail below with reference to the figures.

[0062] Showing:

[0063] Fig. 1 is a schematic representation of two map sections, showing a dynamic area of ​​interest derived from a temporally and spatially variable event as well as various observation points for observing the event;

[0064] Fig. 2 shows a schematic representation of a discretization of a digital road map by a dynamic graph;

[0065] Fig. 3 is a schematic representation of the position of the dynamic area of ​​interest in the dynamic graph at different times;

[0066] Fig. 4 is a schematic representation of a knot chain; and

[0067] Fig. 5 is a schematic representation of an inventive

[0068] Components involved in navigation procedures.

[0069] A navigation method according to the invention makes it possible for the first time to calculate a navigation route 20 (see Figure 5) to a dynamic area of ​​interest 2 or to an observation point 3 for observing a temporally and spatially variable event 1 corresponding to the dynamic area of ​​interest 2. The temporally and spatially variable event 1 is, for example, a periodically variable event such as a sunrise or sunset or an event with a specific time window, such as a parade or a demonstration.

[0070] In Figure 1a), the temporally and spatially variable event 1 is a parade whose parade route is highlighted in bold on a digital street map 6. At different times, the parade procession is located at different locations along the parade route. The locations where the parade procession is located at different times are highlighted in Figure 1a) as individual dynamic areas of interest 2.

[0071] In Figure 1a), an observation point 3 is also shown as an example, from which the parade procession can be “well” observed if it is located exactly in the dynamic area of ​​interest 2, which is outlined with a continuous line in Figure 1a).

[0072] In Figure 1b), the temporally and spatially variable event 1 is a sunset, which can be advantageously observed from the exemplary observation points 3. Depending on the date, the observation points 3 are suggested at different times or locations, so that a user of a navigation device can determine the navigation route 20 and reach the respective observation points 3 in time to observe the sunset. Since the sunset can generally be observed throughout the city, the dynamic area of ​​interest 2 is very large here.

[0073] To map the dynamic areas of interest 2 on the digital road map 6, the digital road map 6 is discretized. This is illustrated using Figure 2. For the sake of clarity, only a few of the similar elements are provided with reference symbols. The digital road map 6 is divided into a plurality of polygons 7, from which a dynamic graph 8 is derived. The dynamic graph 8 comprises a plurality of nodes 9, with each polygon 7 being assigned a node 9. The polygons 7 are adjacent to one another via edges 13. The edges 13 are represented in the dynamic graph 8 by connecting lines 14 between the nodes 9.

[0074] Figure 2 also highlights a dynamic area of ​​interest 2 and one of its neighboring nodes 11. Figure 4 will later explain how a clear view of the dynamic area of ​​interest 2 can be determined using the dynamic graph 8 with the aid of a node chain 12.

[0075] Figure 3 illustrates once again the course of the dynamic area of ​​interest 2 or the temporally and spatially variable event 1 in the digital road map 6 and in the dynamic graph 8 at different times ti, t2, ta and t n .

[0076] A navigation device is capable of calculating a navigation route to the dynamic area of ​​interest 2 or observation point 3. There must be a clear view from observation point 3 to the dynamic area of ​​interest 2 or the temporally and spatially variable event 1. The procedure is illustrated in Figure 4. Starting from the dynamic area of ​​interest 2, node chains 12 are generated radially outward in the dynamic graph 8, with such a node chain 12 being shown representatively in Figures 2 and 4. Each node 9 is assigned height information 10, which describes the topographical height of the terrain or the geodetic height of an object located within the polygon 7. The nature of the height information 10 is illustrated in Figure 4 by its vertical extent.One of the hatched nodes 9 can be selected as observation point 3, since the altitude steadily decreases toward the dynamic area of ​​interest 2. All other nodes 9 of the node chain 12 cannot be considered as observation point 3, since the clear view is blocked by node 9.1. The course of the node chain 12 in the dynamic graph 8 is indicated by arrows in Figures 2 and 4, respectively.

[0077] Figure 5 is a schematic representation of the components involved in the navigation method according to the invention. An event database 4 is provided, in which at least whether the event 1 can be visited and / or observed and when the event 1 occurs and at what location is stored. Corresponding information is forwarded via a data stream 15 to a calculation model 16. Connected to the data stream 15 is a memory 17 for storing metadata about the dynamic areas of interest 2. This metadata can include, in particular: an event category, methods for recognizing the event in the data stream 15, the location of occurrence of the temporally and spatially variable event 1, a method for calculating the temporal development of the event 1, a method for calculating the observation points 3 or

[0078] Observation areas as a function of time, a method for mapping the dynamic areas of interest 2 on a map or a digital road map 6, and other information. The other information includes, for example, which items a user should preferably carry with them in order to participate in the temporally and spatially variable event 1. For example, if event 1 involves plankton glowing due to bioluminescence, the user should pack a swimsuit to be surrounded by the plankton in the ocean.

[0079] Information about temporally and spatially variable events 1 is obtained from an external source 5. For example, source 5.1 is a vehicle in a fleet, source 5.2 is a satellite providing aerial photographs of the dynamic area of ​​interest 2, source 5.3 is a social network, and source 5.4 is a service provider. Information can be obtained via proven interfaces, for example, via the internet using well-known APIs.

[0080] The information is fed into the calculation model 16, which then determines the dynamic areas of interest 2 and observation points 3. Different mathematical models are used for this purpose, depending on the type of information supplied. The spatial and temporal course of periodically occurring events such as sunsets can be calculated using known equations. AI models can be used to predict the location of an elephant herd based on aerial photographs, etc.

[0081] An operating model 18 has access to the calculation model 16. A matching module 19 of the operating model 18 serves as an interface between the calculation model 16 and the navigation route 20 displayed on the navigation device. The calculation model 16 thus calculates or estimates the temporal progression of the dynamic areas of interest 2. Corresponding observation points 3 are also determined for this purpose. Both results are annotated at the front of the dynamic graph 8 and saved. The respective time-dependent points can then be read out by the navigation device, which ultimately allows the determination of the navigation route 20. The components "event database 4" and "calculation model 16" are part of a computing unit (not shown in detail). This can be, in particular, a cloud server or the navigation device itself.The matching module 19 and the calculation of the navigation route 20 then take place in the navigation device itself. The operating model 18 is therefore part of the navigation device.

Claims

Mercedes-Benz Group AG Patent claims 1. Navigation method, wherein a navigation device calculates a navigation route (20) from a starting location to a destination, wherein - a computing unit obtains information about at least one temporally and spatially variable event (1); - the computing unit estimates a temporal-spatial course of the event (1) for a future time horizon and stores it as a dynamic area of ​​interest (2); - the navigation device receives the dynamic area of ​​interest (2), determines a starting location and a starting time and calculates the navigation route (20) from the starting location to the destination, wherein the destination lies within the dynamic area of ​​interest (2) or an observation point (3) is set as the destination from which the event (1) is observable; - the computing unit divides a digital road map (6) into a plurality of polygons (7), wherein map information is assigned to each polygon (7), so that the polygons (7) represent the digital road map (6) in the form of a dynamic graph (8) and the computing unit maps the dynamic area of ​​interest (2) onto the dynamic graph (8), wherein the dynamic graph (8) comprises a plurality of nodes (9), wherein each polygon (7) is assigned a node (9), characterized in that - height information (10) is assigned to the nodes (9) of the graph (8) as map information, wherein the height information (10) describes the topographical height of the terrain and / or the geodetic height of an object located in the respective polygon (7), and the computing unit for each node (9) of the Graphs (8) calculates a height difference to the respective neighboring nodes (11), wherein a clear view to a neighboring node (11) exists if the height to the neighboring node (11) remains the same or decreases; and wherein - the computing unit determines a node chain (12) emanating from the dynamic area of ​​interest (2) with a clear view of the dynamic area of ​​interest (2) and defines a node (9) of the node chain (12) as an observation point (3).

2. Navigation method according to claim 1, characterized in that the computing unit stores information about temporally and spatially variable events (1) in an event database (4), wherein for each event (1) at least the following is stored: - whether the event (1) can be visited and / or observed; and - when the event (1) takes place and where.

3. Navigation method according to claim 1 or 2, characterized in that the computing unit obtains current information about temporally and spatially variable events (1) from at least one of the following sources (5): - a vehicle (5.1) of a networked vehicle fleet; - a satellite (5.2), the satellite providing aerial photographs showing at least part of the dynamic area of ​​interest; - a social network (5.3), where posts about the event are shared on the social network; and / or - a service provider (5.4).

4. Navigation method according to one of claims 1 to 3, characterized in that the computing unit determines several potential observation points (3) and the observation point (3) determined as the destination is selected manually by a user or is selected automatically by the computing unit, so that the travel time and / or travel distance from the starting point to the destination is minimized, in particular taking into account the observation point (3) as an intermediate destination.

5. Navigation method according to one of claims 1 to 4, characterized in that the navigation device recalculates the navigation route (20) during the journey to the destination, in particular taking into account an updated dynamic area of ​​interest (2).

6. Navigation method according to one of claims 1 to 5, characterized in that the navigation device proactively suggests to a user the search for or observation of a temporally and spatially variable event (1) represented by a dynamic area of ​​interest (2), in particular taking into account a user preference, wherein the user preference describes an event category preferred by the user.

7. Navigation system comprising at least one navigation device, in particular an in-vehicle navigation device, characterized in that the navigation device is configured to carry out a method according to one of claims 1 to 6.

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